Biomedical Engineering and Bioengineering Commons^™

Somatic Inhibition By Microscopic Magnetic Stimulation, Hui Ye

Biology: Faculty Publications and Other Works

Electric currents can produce quick, reversible control of neural activity. Externally applied electric currents have been used in inhibiting certain ganglion cells in clinical practices. Via electromagnetic induction, a miniature-sized magnetic coil could provide focal stimulation to the ganglion neurons. Here we report that high-frequency stimulation with the miniature coil could reversibly block ganglion cell activity in marine mollusk Aplysia californica, regardless the firing frequency of the neurons, or concentration of potassium ions around the ganglion neurons. Presence of the ganglion sheath has minimal impact on the inhibitory effects of the coil. The inhibitory effect was local to the …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …

Computational Algorithms For Predicting Membrane Protein Assembly From Angstrom To Micron Scale, Nandhini Rajagopal

Dissertations - ALL

Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications …

Assessment And Diagnosis Of Human Colorectal And Ovarian Cancer Using Optical Imaging And Computer-Aided Diagnosis, Yifeng Zeng

McKelvey School of Engineering Graduate Student Theses & Dissertations

Tissue optical scattering has recently emerged as an important diagnosis parameter associated with early tumor development and progression. To characterize the differences between benign and malignant colorectal tissues, we have created an automated optical scattering coefficient mapping algorithm using an optical coherence tomography (OCT) system. A novel feature called the angular spectrum index quantifies the scattering coefficient distribution. In addition to scattering, subsurface morphological changes are also associated with the development of colorectal cancer. We have observed a specific mucosa structure indicating normal human colorectal tissue, and have developed a real-time pattern recognition neural network to localize this specific structure …

Using Deep Learning To Analyze Materials In Medical Images, Carson Molder

Computer Science and Computer Engineering Undergraduate Honors Theses

Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …

Optimal Analytical Methods For High Accuracy Cardiac Disease Classification And Treatment Based On Ecg Data, Jianwei Zheng

Computational and Data Sciences (PhD) Dissertations

This work constitutes six projects. In the first project, a newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine). This database aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. In the second project, we created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract …

Design And Control Of A Peristaltic Pump To Simulate Left Atrial Pressure In A Conductive Silicone Model, Jeremy Collins

Mechanical Engineering Undergraduate Honors Theses

According to the CDC, atrial fibrillation is responsible for more than 454,000 hospitalizations and approximately 158,000 deaths per year. A common treatment for atrial fibrillation is catheter ablation, a process in which a long flexible tube is guided through the femoral artery and to the source of arrhythmia in the heart, where it measures the electrical potential at various locations and converts problematic heart tissue to scar tissue via ablation. This paper details the design and control of a low-cost ($400) peristaltic pump system using repetitive control to replicate blood pressure in the left atrium in a conductive silicone model …

Development Of Quantitative Ultrasound-Mediated Molecular Imaging Of The Tumor Microenvironment, Trevor Mitcham

Dissertations and Theses (Open Access)

While conventional diagnostic imaging modalities provide anatomical information to clinicians, these techniques are not sensitive to critical physiological processes. In order to properly classify cancer, it is necessary to investigate noninvasive methods which can provide insight into these processes, allowing clinicians to determine personalized therapeutic options. Therefore, molecular imaging is focused on visualization and characterization of biomarkers within the tumor microenvironment (TME), which can then be combined with the anatomical information provided from diagnostic imaging.

Two such biomarkers of interest are blood oxygen saturation (SO₂) and cell receptor expression. SO₂ is a measure of the fraction of …

Biomedical Applications And Syntheses Of Selected Anthraquinone Dyes, Richard Sirard

Senior Honors Theses

Anthraquinones are aromatic organic compounds that have multiple applications in the biomedical field. Some anthraquinone-based compounds are used as fluorophores to contrast cell nuclei while others act as chemotherapeutic agents. However, there are not many fluorescent anthraquinone cell stains currently available. In this study, commercially available anthraquinone dyes, in addition to other dye families and compounds, were reviewed for their unique properties, advantages, and drawbacks. The development and characterization of three novel anthraquinone fluorophores revealed promising photophysical characteristics, like large Stokes shifts. One of the compounds, RBS3, was chosen for fixed and live cell staining and exhibited desirable biomedical properties. …

Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook

Undergraduate Research and Scholarship Symposium

Single-nucleotide polymorphisms (SNPs) are variations in the genome where one base pair can differ between individuals.¹ SNPs occur throughout the genome and can correlate to a disease-state if they occur in a functional region of DNA.¹According to the central dogma of molecular biology, any variation in the DNA sequence will have a direct effect on the RNA sequence and will potentially alter the identity or conformation of a protein product. A single RNA molecule, due to intramolecular base pairing, can acquire a plethora of 3-D conformations that are described by its structural ensemble. One SNP, rs12477830, which …

An Automated Framework For Connected Speech Evaluation Of Neurodegenerative Disease: A Case Study In Parkinson's Disease, Sai Bharadwaj Appakaya

USF Tampa Graduate Theses and Dissertations

Neurodegenerative diseases affect millions of people around the world. The progressive degeneration worsens the symptoms, heavily impacting the quality of life of the patients as well as the caregivers. Speech production is one of the physiological processes affected by neurodegenerative diseases like Alzheimer’s disease, amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). Speech is the most basic form of communication, and the effect of neurodegeneration degrades speech production, thereby reducing social interaction and mental well-being. PD is the second most common neurodegenerative disease affecting speech production in 90% of the diagnosed individuals. Speech analysis methods for PD in clinical methods …

Predictions Of Knee Joint Contact Forces Using Only Kinematic Inputs With A Recurrent Neural Network, Kaileigh Elisabeth Estler

Human Movement Studies & Special Education Theses & Dissertations

BACKGROUND: Knee joint contact (bone on bone) forces are commonly estimated using surrogate measures such as external knee adduction moments (with limited success) or musculoskeletal modeling (more successful). Despite its capabilities, modeling is not optimal for clinicians or persons with limited experience and knowledge. Therefore, the purpose of this study was to design a novel prediction method for knee joint contact forces that is equal or more accurate than modeling, yet simplistic in terms of required inputs. METHODS: This study included all six subjects’ (71.3±6.5kg, 1.7±0.1m) data from the opensource “Grand Challenge” datasets (simtk.org) and two subjects from the "CAMS" …

Analysis Of Inflammation, Metabolic And Clinical Markers In Predicting Fat Mass In Hiv-Positive Males Using Artificial Neural Network, Nurul Farhah Shamsuddin

Student Works (2020-2029)

Increased inflammation has been discovered in people living with Human Immunodeficiency Virus (HIV), which has been associated with the development and advancement of metabolic diseases. Immune activation and inflammation have been revealed to affect the redistribution of fat in people living with HIV (PLWH) whether the individual is on treatment with antiretroviral therapy (ART) or treatment naïve. Therefore, the assessment of body fat composition of PLWH based on markers of inflammation is important to develop keen diagnosis and prognosis of medical conditions facing by these patients, for example lipodystrophy syndrome, metabolic syndrome, dyslipidemia and diabetes mellitus. The purpose of this …

An Improved Clipped Sub-Histogram Equalization Technique Using Optimized Local Contrast Factor For Mammogram Image Analysis, Nurshafira Hazim Chan

Student Works (2020-2029)

Mammography has been known worldwide as the most common imaging modalities utilized for early detection of breast cancer. The mammographic images produced are in greyscale, however they often produced poor contrast images, non-uniform illumination, and the image often contain artefacts and noise. These limitations can be overcame during the pre-processing stage by improving the image enhancement process. Therefore, in this research an optimized enhancement framework is developed where the local contrast factor is manipulated to preserve details of the image. This technique aims to improve the overall image visibility without altering histogram of the original image, which will affect the …

An Investigation Of Cross-Links On Crystallization And Degradation In A Novel, Photocross-Linkable Poly (Lactic Acid) System, Nicholas Baksh

USF Tampa Graduate Theses and Dissertations

Polymeric molecular structure consists of repeating units bonded together. Mechanicalproperties can be altered without affecting chemical makeup by altering the number of these units. Small molecules can be introduced and/or polymers can be modified to form bonds between molecular chains. Cross-linking, as this is called, also introduces mechanical variation with minimal effects on chemical composition. Lastly, polymer chains reorient themselves in response to intermolecular forces. This temperature dependent response is known as crystallization. Although chemistry is unaltered, mechanical properties can depend highly on the percent of the sample that is crystallized.

Cross-linking is known to enhance the mechanical properties of …

Deep Learning-Based Breast Cancer Detection And Classification Using Histopathology Images, Ghulam Murtaza

Student Works (2020-2029)

Cancer disease is drastically increasing worldwide over the past few years. Among all types of cancers in women, breast cancer (BrC) is the main cause of abnormal deaths. For a confident diagnosis of BrC, histopathology (Hp) images are usually suggested by the doctors. BrC detection is a diagnostic test for benign (non-cancerous) and malignant (cancerous) breast tumors (BrT). Once the BrT is diagnosed, then it needs to be classified for subtypes of benign and malignant to start specific treatment. Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training …

Preparation Of Nanoemulsion Using Lipase-Synthesized Glucose Monooleate Through Low Energy Technique, Muhammad Fakhrurazi Ahmad Fadzil

Student Works (2020-2029)

In this study, glucose monooleate (GluO) was synthesized and compared to its counterpart i.e. Tween-80 (Tw-80) and Span-80 (Sp-80) to investigate the influence of the different hydrophilic head structure of the surfactants on emulsification property. Utilizing sugar molecules like glucose as the hydrophilic head group of surfactants is of interest as it has a high potential to be used as a targeted delivery agent. The main objective of this study is to investigate the capability of lipase synthesized GluO in the formation of O/W nanoemulsion in four different types of vegetable oils that are sunflower oil, olive oil, palm oil, …

Principles For Determining The Motion Of Blood Through Arteries, Sylvio R. Bistafa

Euleriana

Translation of Principia pro motu sanguinis per arterias determinando (E855). This work of 1775 by L. Euler is considered to be the first mathematical treatment of circulatory physiology and hemodynamics.

Computational Modelling Enables Robust Multidimensional Nanoscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

The following sections are included:

• Present State of Computational Modelling in Fluorescence Nanoscopy

• Recent Contributions to Computational Modelling in Fluorescence Nanoscopy

• Outlook on Computational Modelling in Fluorescence Nanoscopy

• Acknowledgments

• References

Deep Learning For Task-Based Image Quality Assessment In Medical Imaging, Weimin Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

It has been advocated to use objective measures of image quality (IQ) for assessing and optimizing medical imaging systems. Objective measures of IQ quantify the performance of an observer at a specific diagnostic task. Binary signal detection tasks and joint signal detection and localization (detection-localization) tasks are commonly considered in medical imaging. When optimizing imaging systems for binary signal detection tasks, the performance of the Bayesian Ideal Observer (IO) has been advocated for use as a figure-of-merit (FOM). The IO maximizes the observer performance that is summarized by the receiver operating characteristic (ROC) curve. When signal detection-localization tasks are considered, …

Three-Dimensional (3d) Reconstruction Of Computer Tomography Cardiac Images Using Visualization Toolkit (Vtk), Mohammad Zahid Zamaludin

Student Works (2020-2029)

Cardiac study proves to be important to diagnose and treat cardiovascular disease that accounts for 20% of death in the world. Three-dimensional (3D) images of the heart are important to understand its real structure, functions and physical abnormalities occurring in the tissue. The objective of this paper is to reconstruct 3D images from 2D CT Scan slices of the cardiac region of interest using Visualisation Toolkit (VTK). The Visualization Toolkit (VTK) is non-propriety software with state-of-the-art tools for 3D rendering that is easily customizable programming. 3D images are reconstructed using surface rendering technique and volume rendering technique. Volume rendering shows …

A Hybrid Gene Selection Strategy Based On Fisher And Ant Colony Optimization Algorithm For Breast Cancer Classification, Mohammed Hamim, Ismail El Moudden, Mohan D. Pant, Hicham Moutachaouik, Mustapha Hain

EVMS School of Health Professions Faculty Publications

Breast cancer poses the greatest threat to human life and especially to women's life. Despite the progress made in data mining technology in recent years, the ability to predict and diagnose such fatal diseases based on gene expression data still reveals a limited prediction performance, which may not be surprising since most of the genes in expression data are believed to be irrelevant or redundant. The dimensionality reduction process may be considered as a crucial step to analyze gene expression data, as it can reduce the high dimensionality of the breast cancer datasets, which may result into a better prediction …

Fluid Model Of Plasma-Liquid Interaction: The Effect Of Interfacial Boundary Conditions And Henry's Law Constants, Yifan Liu, Dingxin Liu, Jishen Zhang, Bowen Sun, Santu Luo, Hao Zhang, Li Guo, Mingzhe Rong, Michael G. Kong

Bioelectrics Publications

Plasma–liquid interaction is a critical area of plasma science, mainly because much remains unknown about the physicochemical processes occurring at the plasma–liquid interface. Besides a lot of experimental studies toward the interaction, a few fluid models have also been reported in recent years. However, the interfacial boundary conditions in the models are different and the Henry's law constants therein are uncertain; hence, the accuracy and robustness of the simulation results are doubtable. In view of this, three 1D fluid models are developed for the interaction between a plasma jet and deionized water, each of which has a unique interfacial boundary …

Oxygen Harvesting From Carbon Dioxide: Simultaneous Epoxidation And Co Formation, Han Xu, Muhammad Shaban, Sui Wang, Anas Alkayal, Dingxin Liu, Michael G. Kong, Felix Plasser, Benjamin R. Buckley, Felipe Iza

Bioelectrics Publications

Due to increasing concentrations in the atmosphere, carbon dioxide has, in recent times, been targeted for utilisation (Carbon Capture Utilisation and Storage, CCUS). In particular, the production of CO from CO₂ has been an area of intense interest, particularly since the CO can be utilized in Fischer–Tropsch synthesis. Herein we report that CO₂ can also be used as a source of atomic oxygen that is efficiently harvested and used as a waste-free terminal oxidant for the oxidation of alkenes to epoxides. Simultaneously, the process yields CO. Utilization of the atomic oxygen does not only generate a valuable product, …

Discharge Mode Transition In He/Ar Atmospheric Pressure Plasma Jet And Its Inactivation Effect Against Tumor Cells In Vitro, Bolun Pang, Zhijie Liu, Sitao Wang, Yuting Gao, Huaiyan Zhang, Feng Zhang, Xiamin Tantai, Dehui Xu, Dingxin Liu, Michael G. Kong

Bioelectrics Publications

Discharge characteristic comparisons between He and Ar plasma jets have been extensively reported, but is rarely reported for the comprehensive study of discharge mode transition from He jet to Ar jet, especially its induced liquid chemistry and biological effect. In this paper, we investigate the plasma jet mode transformation by varying the Ar contents in the He/Ar mixing working gas, particularly focusing on the effect of liquid chemistry of plasma activated water (PAW) and the corresponding inactivation effect against tumor cells in vitro. The mode transition process from He jet to Ar jet is characterized by the discharge images, …

Photodynamic Therapy Of Inorganic Complexes For The Treatment Of Cancer, Chloe B. Smith, Lindsay C. Days, Duaa R. Alajroush, Khadija Faye, Yara Khodour, Stephen J. Beebe, Alvin Holder

Chemistry & Biochemistry Faculty Publications

Photodynamic therapy (PDT) is a medicinal tool that uses a photosensitiser and a light source to treat several conditions, including cancer. PDT uses reactive oxygen species (ROS) such as cytotoxic singlet oxygen ¹O₂ to induce cell death in cancer cells. Chemotherapy has historically utilized the cytotoxic effects of many metals, especially transition-metal complexes. However, chemotherapy is a systemic treatment so all cells in a patient's body are exposed to the same cytotoxic effects. Transition metal complexes have also shown high cytotoxicity as PDT agents. PDT is a potential localized method for treating several cancer types by using inorganic …

Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya

Honors Theses

Magnetic resonance imaging (MRI) can help visualize various brain regions. Typical MRI sequences consist of T1-weighted sequence (favorable for observing large brain structures), T2-weighted sequence (useful for pathology), and T2-FLAIR scan (useful for pathology with suppression of signal from water). While these different scans provide complementary information, acquiring them leads to acquisition times of ~1 hour and an average cost of $2,600, presenting significant barriers. To reduce these costs associated with brain MRIs, we present pTransGAN, a generative adversarial network capable of translating both healthy and unhealthy T1 scans into T2 scans. We show that the addition of non-adversarial …

Applied Machine Learning In Extrusion-Based Bioprinting, Shuyu Tian

Theses and Dissertations

Optimization of extrusion-based bioprinting (EBB) parameters have been systematically conducted through experimentation. However, the process is time and resource-intensive and not easily translatable across different laboratories. A machine learning (ML) approach to EBB parameter optimization can accelerate this process for laboratories across the field through training using data collected from published literature. In this work, regression-based and classification-based ML models were investigated for their abilities to predict printing outcomes of cell viability and filament diameter for cell-containing alginate and gelatin composite hydrogels. Regression-based models were investigated for their ability to predict suitable extrusion pressure given desired cell viability when keeping …

Nebulizer-Based Systems To Improve Pharmaceutical Aerosol Delivery To The Lungs, Benjamin M. Spence

Theses and Dissertations

Combining vibrating mesh nebulizers with additional new technologies leads to substantial improvements in pharmaceutical aerosol delivery to the lungs across therapeutic administration methods. In this dissertation, streamlined components, aerosol administration synchronization, and/or Excipient Enhanced Growth (EEG) technologies were utilized to develop and test several novel devices and aerosol delivery systems. The first focus of this work was to improve the poor delivery efficiency, e.g., 3.6% of nominal dose (Dugernier et al. 2017), of aerosolized medication administration to adult human subjects concurrent with high flow nasal cannula (HFNC) therapy, a form of continuous-flow non-invasive ventilation (NIV). The developed Low-Volume Mixer-Heater (LVMH) …

Biocybersecurity: A Converging Threat As An Auxiliary To War, Lucas Potter, Orlando Ayala, Xavier-Lewis Palmer

Engineering Technology Faculty Publications

Biodefense is the discipline of ensuring biosecurity with respect to select groups of organisms and limiting their spread. This field has increasingly been challenged by novel threats from nature that have been weaponized such as SARS, Anthrax, and similar pathogens, but has emerged victorious through collaboration of national and world health groups. However, it may come under additional stress in the 21st century as the field intersects with the cyberworld-- a world where governments have already been struggling to keep up with cyber attacks from small to state-level actors as cyberthreats have been relied on to level the playing field …